检索结果-内蒙古大学图书馆

GAN-DIRNet:A Novel Deformable Image Registration Approach for Multimodal Histological Images

computers, Materials & Continua 2024年第7期80卷 487-506页

作者： Haiyue Li Jing Xie Jing Ke Ye Yuan Xiaoyong Pan Hongyi Xin Hongbin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai200240China Department of Pathology Ruijin HospitalShanghai Jiao Tong UniversitySchool of MedicineShanghai200025China Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Global Institute of Future Technology Shanghai Jiao Tong UniversityShanghai200240China

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of *** neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image ***,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s *** argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator *** this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image *** begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific ***,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise ***,experiments and evaluations were conducted on the registration of the Mixed National Institute of Standards and technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s *** results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

关键词： Histological images registration deformable registration generative adversarial network cushing’s disease machine learning computer vision

来源：评论

学校读者我要写书评

暂无评论

The Power of Bamboo: On the Post-Compromise Security for Searchable Symmetric Encryption 30

The Power of Bamboo: On the Post-Compromise Security for Sea...

引用

30th Annual Network and Distributed system Security Symposium, NDSS 2023

作者： Chen, Tianyang Xu, Peng Picek, Stjepan Luo, Bo Susilo, Willy Jin, Hai Liang, Kaitai National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering China Cluster and Grid Computing Lab School of Computer Science and Technology China Huazhong University of Science and Technology Wuhan430074 China Digital Security Group Radboud University Nijmegen Netherlands Department of EECS Institute of Information Sciences The University of Kansas LawrenceKS United States Institute of Cybersecurity and Cryptology School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft2628 CD Netherlands

ISBN: (纸本)1891562835

Dynamic searchable symmetric encryption (DSSE) enables users to delegate the keyword search over dynamically updated encrypted databases to an honest-but-curious server without losing keyword privacy. This paper studies a new and practical security risk to DSSE, namely, secret key compromise (e.g., a user’s secret key is leaked or stolen), which threatens all the security guarantees offered by existing DSSE schemes. To address this open problem, we introduce the notion of searchable encryption with key-update (SEKU) that provides users with the option of non-interactive key updates. We further define the notion of post-compromise secure with respect to leakage functions to study whether DSSE schemes can still provide data security after the client’s secret key is compromised. We demonstrate that post-compromise security is achievable with a proposed protocol called "Bamboo". Interestingly, the leakage functions of Bamboo satisfy the requirements for both forward and backward security. We conduct a performance evaluation of Bamboo using a real-world dataset and compare its runtime efficiency with the existing forward-and-backward secure DSSE schemes. The result shows that Bamboo provides strong security with better or comparable performance. © 2023 30th Annual Network and Distributed system Security Symposium, NDSS 2023. All Rights Reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Efficient Hybrid PAPR Reduction for 5G NOMA-FBMC Waveforms

引用

computers, Materials & Continua 2021年第12期69卷 2967-2981页

作者： Arun Kumar Sivabalan Ambigapathy Mehedi Masud Emad Sami Jaha Sumit Chakravarty Kanchan Sengar Department of Electronics and Communication Engineering JECRC UniversityJaipur303905India Center for System Design Chennai Institute of TechnologyIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Computer Engineering Kennesaw State UniversityGAUSA

The article introduces Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC),known as hybrid waveform(NOMAFBMC),as two of the most deserving contenders for fifth-generation(5G)*** spectrum access and clampdown of spectrum outflow are unique characteristics of hybrid *** compare the spectral efficiency of Orthogonal Frequency Division Multiplexing(OFDM),FBMC,NOMA,and *** is seen that the hybrid waveform outperforms the existing *** to Average Power Ratio(PAPR)is regarded as a significant issue in multicarrier *** combination of Selective Mapping-Partial Transmit Sequence(SLM-PTS)is an effective way to minimize large peak power *** SLM,PTS,and SLM-PTS procedures are applied to the NOMA-FBMC *** hybrid structure is applied to the existing ***,the correlated factors like Bit Error Rate(BER)and Computational Overhead(CO)are studied and computed for these *** outcome of the work reveals that the NOMA-FBMC waveform coupled with the SLM-PTS algorithm offers superior performance as compared to the prevailing systems.

关键词： 5G NOMA-FBMC SLM-PTS PAPR BER OFDM

来源：评论

学校读者我要写书评

暂无评论

Skin cancer detection using deep machine learning techniques

引用

Intelligence-Based Medicine 2025年 11卷 100191-100191页

作者： Akinrinade, Olusoji Du, Chunglin Computer System Engineering Department Tshwane University of Technology South Africa University Soshaguve South Africa

Technological advancements have allowed people to have unfettered access to the internet from anywhere in the world. However, there is still little access to healthcare in rural and remote areas. This study highlights the potential of deep learning techniques in improving the early detection of skin cancer, a condition affecting millions globally. By addressing the challenges of class imbalance and dataset limitations, this research presents a model that can be integrated into digital health platforms, potentially saving lives by enabling earlier diagnosis and intervention, especially in underserved regions. The study also suggest using deep learning and few-shot learning when using machine learning techniques for skin cancer diagnosis. This study utilized a novel approach the use of raw images for training and test images for test data. These input images were then pre-processed using a deep model to identify and predict subsequent outputs using the model. In addition, the effect of the Convolutional Neural Network (CNN) effect in predicting accuracy using a skin lesion's texture to differentiate between benign and malignant lesions in the body was also examined using retrieved image elements from skin photos that were significant to skin cancer identification. The study focuses on using deep learning techniques to improve the detection of skin cancer from dermoscopic images. Deep learning a top-tier method for classifying skin lesions, was applied to create an end-to-end algorithm that could identify skin cancer more accurately. A variety of deep learning backbones were utilized, addressing the challenge of class imbalance in large datasets and seeking ways to boost performance even when only small datasets are available. To overcome these obstacles, the research leveraged transfer learning, data augmentation, and Generative Adversarial Networks (GANs). It further explored different sampling techniques and loss functions that could be effective for imbalanced data

关键词： Accuracy Artificial intelligence Diseases Machine learning Patterns Skin cancer Skin detection

来源：评论

学校读者我要写书评

暂无评论

Studying of Machine Learning Models for Forecasting Macroeconomic Indicators 27

Studying of Machine Learning Models for Forecasting Macroeco...

引用

27th International Conference on Advanced Communications technology, ICACT 2025

作者： Ngoc, Lan Dong Thi Ngo-Thi-Thu-Trang Kim, Kyoung-Mok Pham, Vung Nguyen, Ha-Nam Department of Economic Information System Academy of Finance Hanoi Viet Nam Faculty of Information Technology University of Engineering and Technology Vietnam National University Hanoi Viet Nam Posts and Telecommunications Institute of Technology Hanoi122300 Viet Nam Computer Science Department Sam Houston State University HuntsvilleTX77340 United States Department of Medical Information Sahmyook Health University Seoul Korea Republic of Faculty of Information Technology Electric Power University Hanoi Viet Nam

ISBN: (纸本)9791188428137

This study explores the application of machine learning models in forecasting macro-economic indicators, including GDP, inflation rate, unemployment rate, and exchange rate across 11 Southeast Asian countries. The models used include Linear Regression, ARIMA, Random Forest, XGBoost, LSTM, and SVM. We conducted a performance comparison of each model based on MAE, RMSE, and R2 metrics to evaluate the accuracy of the forecasts. The experimental results indicate that Random Forest and XGBoost models excel in predicting nonlinear and complex indicators such as GDP and unemployment rate, while ARIMA and Linear Regression models perform better in time series with clear regular patterns, like inflation rate. The LSTM model shows inconsistent effective-ness, requiring large data volumes and complex optimization processes. SVM demonstrates potential in handling nonlinear data but requires careful tuning. This study concludes that using machine learning models presents significant potential for improving the accuracy of macroeconomic forecasting. However, model tuning and optimization are essential to match the characteristics of each type of economic indicator. Future research directions include developing hybrid models and integrating additional factors such as market sentiment, social and environmental indicators (ESG) to enhance forecasting outcomes. Copyright 2025 Global IT Research Institute (GIRI). All rights reserved.

关键词： Inflation

来源：评论

学校读者我要写书评

暂无评论

Personalized Collaborative Search Engine for Decision Making

Personalized Collaborative Search Engine for Decision Making

引用

Communication, computer Sciences and engineering (IC3SE), International Conference on

作者： Mohd. Murshleen Prabhu A Garima Jain Department of Computer Science and Engineering Tula's Institute Dehradun India Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Computer Science & Business System Noida Institute of Engineering and Technology Greater Noida Uttar Pradesh India

ISBN: (数字)9798350366846

ISBN: (纸本)9798350366853

Web search engines are used for retrieving information but still there exists ambiguity in their retrieval process. It is so because traditional search engines laid emphasis on matching of keywords rather than maintaining semantic relations among terms lack of ability to produce precise results, presence of ambiguous keywords and verifying needs of users are few hindrances that are acting as scenario for web search engines. The paper focuses on improving search quality of users by collecting user experiences through creating hierarchical user profile it leads to collaborative search engine that helps in reaching at particular decision then the collected user's data are uploaded to recommendation server which are than displayed a search engines like Google/Yahoo.

关键词： Semantics Decision making Collaboration Search engines Servers Web search Engines

来源：评论

学校读者我要写书评

暂无评论

Security Issues and Workable Solutions in the Context of Sensor Cloud

Security Issues and Workable Solutions in the Context of Sen...

引用

Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI), International Conference on

作者： Sanjeev Kumar Mandal Manali Gupta Braiehdra Sharma Department of Computer Science and Information Technology Jain (Deemed to be University) Bangalore India Department of Computer Science & Business System Noida Institute Of Engineering and Technology Greater Noida Uttar Pradesh India Department of Computer Science and Engineering Tula's Institute Dehradun India

ISBN: (数字)9798350355338

ISBN: (纸本)9798350355345

Notable tech companies such as Facebook, Microsoft, Apple, Google, and a number of game companies have launched bold plans to bring the metaverse to life. It is inevitable that in the years to come, virtual worlds will change significantly as a result of the metaverse ecosystem's ongoing enhancement and the rapid advancement of new technology. Nonetheless, a great deal of work still has to be done before the metaverse can be incorporated into our everyday lives and physical reality. This paper explores the metaverse's rising importance in the area of medicine and looks at its technological roadmap. We see a metaverse having the potential to drastically change intelligent health care facilities in the future, ushering in a new age of creative healthcare solutions.

关键词： Cloud computing Metaverse Social networking (online) Computational modeling Medical services Companies Games Predictive models Security Context modeling

来源：评论

学校读者我要写书评

暂无评论

Accumulative Time Based Ranking Method to Reputation Evaluation in Information Networks

引用

Journal of computer Science & technology 2022年第4期37卷 960-974页

作者： Hao Liao Qi-Xin Liu Ze-Cheng Huang Ke-Zhong Lu Chi Ho Yeung Yi-Cheng Zhang National Engineering Laboratory on Big Data System Computing Technology College of Computer Science and SoftwareEngineeringShenzhen UniversityShenzhen 518060China Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen UniversityShenzhen 518060China Guangdong Province Engineering Center of China-Made High Performance Data Computing System College of ComputerScience and Software EngineeringShenzhen UniversityShenzhen 518060China Institute of Big Data Intelligent Management and Decision Shenzhen UniversityShenzhen 518060China Department of Science and Environmental Studies The Education University of Hong KongHong Kong 999077China Department of Physics University of FribourgFribourg 1700Switzerland

Due to over-abundant information on the Web, information filtering becomes a key task for online users to obtain relevant suggestions and how to extract the most related item is always a key topic for researchers in various fields. In this paper, we adopt tools used to analyze complex networks to evaluate user reputation and item quality. In our proposed Accumulative Time Based Ranking (ATR) algorithm, we take into account the growth record of the network to identify the evolution of the reputation of users and the quality of items, by incorporating two behavior weighting factors which can capture the hidden facts on reputation and quality dynamics for each user and item respectively. Our proposed ATR algorithm mainly combines the iterative approach to rank user reputation and item quality with temporal dependence compared with other reputation evaluation methods. We show that our algorithm outperforms other benchmark ranking algorithms in terms of precision and robustness on empirical datasets from various online retailers and the citation datasets among research publications. Therefore, our proposed method has the capability to effectively evaluate user reputation and item quality.

关键词： temporal network behavior dynamics reputation evaluation ranking algorithm

来源：评论

学校读者我要写书评

暂无评论

A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

引用

作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of Control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic Control Society.

关键词： Trucks

来源：评论

学校读者我要写书评

暂无评论

Detecting Retinal Nerve Fiber Layer Using Gray Level Co-occurrence Matrix and Machine Learning Approach

Detecting Retinal Nerve Fiber Layer Using Gray Level Co-occu...

引用

2022 International Conference on Information technology Research and Innovation, ICITRI 2022

作者： Septiarini, Anindita Hamdani, Hamdani Setyaningsih, Emy Maharani, Septya Munir, Aam Shodiqul Winarno, Edy Mulawarman University Faculty of Engineering Department of Informatics Samarinda Indonesia Institut Sains Teknologi AKPRIND Department of Computer System Engineering Yogyakarta Indonesia Universitas Stikubank Faculty of Information Technology Semarang Indonesia

ISBN: (数字)9781665461849

ISBN: (纸本)9781665461849

The retinal nerve fiber layer (RNFL) is the white scratch part in the fundus image. It could be an indicator of several diseases characterized by depletion of RNFL. This study intends to construct an RNFL method using Gray Level Cooccurrence Matrix (GLCM) as texture features and implementing random forest as the classifier. The approach has four primary steps: defining the region of interest (ROI), forming the area of features extraction, pre-processing, feature extraction, and classification. Forming the ROI was applied through two main steps: The segmentation with K-means clustering and dividing the fundus image into 12 sub-sectors. The image was then turned into a grayscale as part of the pre-processing. Afterward, the features were extracted using GLCM, followed by features reduction with Correlation-based Feature Selection (CFS). The last step was to use the artificial neural network (ANN) method to classify the data. In this study, the RNFL detection method achieved the accuracy value of 96.7% against the dataset consisting of 40 images. © 2022 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：